2026-05-30T10:44:26Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

c1be2c795629985e7e38c3621ddc005089847479e9554fc3d4e0011be649952c 2025-12-08T01:52:51Z language:enopenaire_data

A true denial or a false confession? Assessing veracity of suspects' statements using MASAM and SVA A true denial or a false confession? Assessing veracity of suspects' statements using MASAM and SVA doi:10.17026/DANS-ZAN-2K9Xeasy-dataset:77877 B.W. Wojciechowski 2018-01-30 DANS Data Station Social Sciences and Humanities 2018-01-31 LawSocial SciencesTrue and false statementsOffendersConfessions and denialsVeracity of suspects' statementsMultivariable Adults' Statements Assessment ModelStatement Validity Assessment <p>Previous research on statement analysis has mainly concerned accounts by witnesses and plaintiffs. In our studies we examined true and false statements as told by offenders. It was hypothesized that SVA and MASAM techniques would enhance the ability to discriminate between true and false offenders' statements. Truthful and deceptive statements (confessions and denials) were collected from Swedish and Polish criminal case files. In Experiment 1, Swedish law students (N = 39) were asked to assess the veracity of statements either after training in and usage of MASAM or without any training and using their own judgements. In Experiment 2, Polish psychology students (N = 36) assessed veracity after training in and usage of either MASAM or SVA or without prior training using their own judgements. The veracity assessments of participants who used MASAM and SVA were significantly more correct than the assessments of participants that used their own judgements. The highest accuracy rate was for true confessions using MASAM (77,53%) and the lowest accuracy rate was for false denials using MASAM (38,78%). Both total SVA and MASAM scores differentiated between lies and truths. The criteria most strongly associated with correct assessments were: logical structure, contextual embedding, self - depreciation, volume of statement, contextual setting and descriptions of relations. Results show, that SVA is a better lie detection tool, than MASAM and trained coders are better at distinguishing between truths and lies than lay evaluators. The results are discussed in relation to statement analysis of offenders' accounts.</p> https://ssh.datastations.nl/oai doi:10.17026/DANS-ZAN-2K9X 2025-12-03T01:00:47Z ddi:codebook:2_5